Mohammad E Khodayar, Ph.D.

Dr. Mohammad Khodayar  

Mohammad E Khodayar, Ph.D.

Associate Professor of Electrical & Computer Engineering

Office Location: Junkins 334

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Education

  • Ph.D. Electrical Engineering – Illinois Institute of Technology
  • MS Electrical Engineering –Sharif University of Technology
  • BS Electrical Engineering – Amirkabir University of Technology (Tehran Polytechnic)

Biography

Mohammad E. Khodayar received the B.Sc. and M.Sc. degrees in electrical engineering from Amirkabir University of Technology (Tehran Polytechnic) and Sharif University of Technology, respectively; and the Ph.D. degree in electrical engineering from Illinois Institute of Technology, Chicago, IL, USA, in 2012. He was a Senior Research Associate in the Robert W. Galvin Center for Electricity Innovation at Illinois Institute of Technology. He is currently an Associate Professor with the Department of Electrical and Computer Engineering, at 51做厙, Dallas, TX, USA. He served on the editorial board of several IEEE journals including IEEE Transactions on Sustainable Energy, IEEE Transactions on Smart Grid, IEEE Power Engineering Letters and IEEE Access. He is an associate editor of the IEEE Transactions on Vehicular Technology and IEEE Transactions on Transportation Electrification. His research interests include power system operation and planning, transportation electrification, and applications of machine learning to power systems. He has published over 60 peer reviewed journals in well-respected journals. His research was supported by National Science Foundation and Department of Energy.

Honors and Awards

  • World's Top 2% Scientists ranking published by Stanford University in 2021 and 2022.

Research

  • Power System Operation and Planning
  • Infrastructure Resilience
  • Energy Hubs
  • Transportation Electrification
  • Cyber-Physical Systems
  • Artificial Intelligence

Recent Publications

  • M. Saffari, M. Khodayar, M. E. Khodayar, M. Shahidehpour, “Behind-the-Meter Load and PV Disaggregation via Deep Spatiotemporal Graph Generative Sparse Coding with Capsule Network” IEEE Transactions on Neural Networks and Learning Systems, Early Access.
  • A. H. Alobaidi, S. S. Fazlhashemi, M. Khodayar, J. Wang, M. E. Khodayar, “Distribution service restoration with renewable energy sources: a review” IEEE Transactions on Sustainable Energy, vol. 14, no. 2, pp. 1151-1168, 2023.
  • J. Li, M. E. Khodayar, J. Wang, B. Zhou, “Data-driven distributionally robust co-optimization of P2P energy trading and network operation for interconnected microgrids”, IEEE Transactions on Smart Grid vol. 12, no. 6, pp. 5172-5184, 2021.
  • M. Khodayar, G. Liu, J. Wang, O. Kaynak, M. E. Khodayar, “Spatiotemporal behind-the-meter load and PV power forecasting via deep graph dictionary learning” IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 10, pp. 4713-4727, 2020.
  • S. D. Manshadi, M. E. Khodayar, “Strategic behavior of in-motion wireless charging aggregators in the electricity and transportation networks” IEEE Transactions on Vehicular Technology, vol. 69, no. 12, pp. 14780-14792, 2020.

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